Update README

README.md

@@ -6,16 +6,30 @@ widget:
 
 # BERT Base for Tigrinya Language
 
-We pretrain a BERT base-uncased model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs.
+We pre-train a BERT base-uncased model for Tigrinya on a dataset of 40 million tokens trained for 40 epochs.
 
-Contained in this repo is the original pretrained Flax model that was trained on a TPU v3.8 and it's corresponding PyTorch version.
+This repo contains the original pre-trained Flax model that was trained on a TPU v3.8 and its corresponding PyTorch version.
 
 ## Hyperparameters
 
-The hyperparameters corresponding to model sizes mentioned above are as follows:
+The hyperparameters corresponding to the model sizes mentioned above are as follows:
 
 | Model Size | L  | AH | HS  | FFN  | P    | Seq  |
 |------------|----|----|-----|------|------|------|
 | BASE       | 12 | 12 | 768 | 3072 | 110M | 512  |
 
 (L = number of layers; AH = number of attention heads; HS = hidden size; FFN = feedforward network dimension; P = number of parameters; Seq = maximum sequence length.)
+
+
+## Citation
+
+If you use this model in your product or research, please cite as follows:
+
+```
+@article{Fitsum2021TiPLMs,
+  author={Fitsum Gaim and Wonsuk Yang and Jong C. Park},
+  title={Monolingual Pre-trained Language Models for Tigrinya},
+  year=2021,
+  publisher={WiNLP 2021 at EMNLP 2021}
+}
+```